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題名 追蹤資料分量迴歸之內生性問題
Panel Data Quantile Regression with Endogeneity作者 朱韋杰
Chu, Wei-Chieh貢獻者 林馨怡
Lin, Hsin-Yi
朱韋杰
Chu, Wei-Chieh關鍵詞 分量迴歸
追蹤資料
內生性日期 2018 上傳時間 3-Jul-2018 17:33:51 (UTC+8) 摘要 本文結合 Canay(2011)和 Lee(2007)的做法，提出三階段估計，以解決追蹤資料分量迴歸模型的內生性問題。本論文提出的方法具有估計簡便且計算快速的優點，同時本論文利用數學證明其大樣本性質。最後，經由蒙地卡羅(Monte Carlo)模擬，本論文發現，在小樣本之下，本論文提出的三階段估計確實可以有效解決追蹤資料分量迴歸內生性問題。三階段估計相較於文獻的其他估計方法，可大幅地減少估計時間。 參考文獻 Amemiya, A., Angrist, J.D., Imbens, G.W., 2006, Instrumental Variables estimates of the effect of subsidized training on the quantiles of trainee earnings. Econo-metrica, 70, 91–117.\nCanay, I.A., 2011, A simple approach to quantile regression for panel data. Econometrics Journal, 14, 368–386.\nChernozhukov, V., and C. Hansen, 2005, An IV model of quantile treatment effects.Econometrica, 73, 245–261.\nChernozhukov, V., and C. Hansen, 2006, Instrumental quantile regression inference for structural and treatment effect models. Journal of Econometrics, 123, 491–525.\nChesher, A.D., 2003, Identification in nonseparable models. Econometrica, 71, 1405–1441.\nGalvao, A.F., 2011, Quantile regression for dynamic data with fixed effects. Journal of Econometrics, 164, 142–157.\nGalvao, A.F., and Montes-Rojas, G.V., 2010, Penalized Quantile regression for dynamic panel data. Journal of Statistical Planning and Inference, 140, 3476–3497.\nHarding, M., and Lamarche, C.,2009, A quantile regression approach for estimating panel data models using instrumental variables. Economics Letters, 104, 133–135.\nHong, H., and Tamer, E., 2003, Inference in censored models with endogenous regressors. Econometrica, 71, 905–932.\nImbens, G.W., and Newwy, W.K., 2003, Identification and estimation of triangular simultaneous equations models without additivity. MIT working paper.\nKoenker, R., 2004, Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91, 74–89.\nKoenker, R. and G. Bassett, 1978, Regression quantiles. Econometrica, 46, 33–50.\nLee, S., 2007, Endogeneity in quantile regression models : A control function approach. Journal of Econometrics, 141, 1131–1158.\nNewey, W.K., Powell, J.L., and J.L., Vella, 1999, Nonparametric estimation of triangular simultaneous equations model. Econometrica, 67, 565–603.\nvan der Vaart, A. W. 1998, Asymptotic Statistic. Cambridge:Cambridge University Press.\nvan der Vaart, A. W. and J. A. Wellner W. 1996, Weak Convergence and Empirical Processes. New York : SpringerVerlag. 描述 碩士
國立政治大學
經濟學系
105258030資料來源 http://thesis.lib.nccu.edu.tw/record/#G0105258030 資料類型 thesis dc.contributor.advisor 林馨怡 zh_TW dc.contributor.advisor Lin, Hsin-Yi en_US dc.contributor.author (Authors) 朱韋杰 zh_TW dc.contributor.author (Authors) Chu, Wei-Chieh en_US dc.creator (作者) 朱韋杰 zh_TW dc.creator (作者) Chu, Wei-Chieh en_US dc.date (日期) 2018 en_US dc.date.accessioned 3-Jul-2018 17:33:51 (UTC+8) - dc.date.available 3-Jul-2018 17:33:51 (UTC+8) - dc.date.issued (上傳時間) 3-Jul-2018 17:33:51 (UTC+8) - dc.identifier (Other Identifiers) G0105258030 en_US dc.identifier.uri (URI) https://ah.lib.nccu.edu.tw/item?item_id=136089 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 經濟學系 zh_TW dc.description (描述) 105258030 zh_TW dc.description.abstract (摘要) 本文結合 Canay(2011)和 Lee(2007)的做法，提出三階段估計，以解決追蹤資料分量迴歸模型的內生性問題。本論文提出的方法具有估計簡便且計算快速的優點，同時本論文利用數學證明其大樣本性質。最後，經由蒙地卡羅(Monte Carlo)模擬，本論文發現，在小樣本之下，本論文提出的三階段估計確實可以有效解決追蹤資料分量迴歸內生性問題。三階段估計相較於文獻的其他估計方法，可大幅地減少估計時間。 zh_TW dc.description.tableofcontents 1 緒論 1\n2 文獻回顧 3\n2.1 分量迴歸模型與內生性問題 3\n2.2 追蹤資料分量迴歸模型 6\n3 理論模型 12\n3.1 理論模型 12\n3.2 證明 17\n4 蒙地卡羅模擬 25\n4.1 模擬設定 25\n4.2 模擬結果 26\n5 結論 39 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0105258030 en_US dc.subject (關鍵詞) 分量迴歸 zh_TW dc.subject (關鍵詞) 追蹤資料 zh_TW dc.subject (關鍵詞) 內生性 zh_TW dc.title (題名) 追蹤資料分量迴歸之內生性問題 zh_TW dc.title (題名) Panel Data Quantile Regression with Endogeneity en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) Amemiya, A., Angrist, J.D., Imbens, G.W., 2006, Instrumental Variables estimates of the effect of subsidized training on the quantiles of trainee earnings. Econo-metrica, 70, 91–117.\nCanay, I.A., 2011, A simple approach to quantile regression for panel data. Econometrics Journal, 14, 368–386.\nChernozhukov, V., and C. Hansen, 2005, An IV model of quantile treatment effects.Econometrica, 73, 245–261.\nChernozhukov, V., and C. Hansen, 2006, Instrumental quantile regression inference for structural and treatment effect models. Journal of Econometrics, 123, 491–525.\nChesher, A.D., 2003, Identification in nonseparable models. Econometrica, 71, 1405–1441.\nGalvao, A.F., 2011, Quantile regression for dynamic data with fixed effects. Journal of Econometrics, 164, 142–157.\nGalvao, A.F., and Montes-Rojas, G.V., 2010, Penalized Quantile regression for dynamic panel data. Journal of Statistical Planning and Inference, 140, 3476–3497.\nHarding, M., and Lamarche, C.,2009, A quantile regression approach for estimating panel data models using instrumental variables. Economics Letters, 104, 133–135.\nHong, H., and Tamer, E., 2003, Inference in censored models with endogenous regressors. Econometrica, 71, 905–932.\nImbens, G.W., and Newwy, W.K., 2003, Identification and estimation of triangular simultaneous equations models without additivity. MIT working paper.\nKoenker, R., 2004, Quantile regression for longitudinal data. Journal of Multivariate Analysis, 91, 74–89.\nKoenker, R. and G. Bassett, 1978, Regression quantiles. Econometrica, 46, 33–50.\nLee, S., 2007, Endogeneity in quantile regression models : A control function approach. Journal of Econometrics, 141, 1131–1158.\nNewey, W.K., Powell, J.L., and J.L., Vella, 1999, Nonparametric estimation of triangular simultaneous equations model. Econometrica, 67, 565–603.\nvan der Vaart, A. W. 1998, Asymptotic Statistic. Cambridge:Cambridge University Press.\nvan der Vaart, A. W. and J. A. Wellner W. 1996, Weak Convergence and Empirical Processes. New York : SpringerVerlag. zh_TW dc.identifier.doi (DOI) 10.6814/THE.NCCU.ECONO.001.2018.F06 -
